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841 results for “vibrations”
Data Associated with the paper "Bell correlations between light and vibration"
<p>Data Associated with the <a href="http://doi.org/10.1126/sciadv.abb0260">following paper</a></p> <blockquote> <p>S. Tarrago Velez, V. Sudhir, N. Sangouard, C. Galland, Bell correlations between light and vibration at ambient conditions. Sci. Adv. 6, eabb0260 (2020).</p> </blockquote> <p>A thorough explanation of the experiment performed is available there.</p> <p> </p> <p>The file <strong>RawData_DelaySweep.zip</strong> contains the raw count information as obtained during the experiment. It is organized in different folders, each containing the data associated with one particular position of the delay stage. The file naming convention has the position, followed by the angles in detection (thA corresponds to the Stokes detection arm and thB corresponds to the anti-Stokes detection arm), and the acquisition time. As explained in the Supplementary Information Sec. 2.1, there are multiple measurements for each combination of delay and detection settings. The zip file also contains the file AnalysisBellv3.py, which was used to analyze the data. Running the file produces 'resultsBell.txt' and 'results_g2.txt', which contain the results for the CHSH parameter and the second order cross correlation, respectively.</p> <p> </p> <p>The file <strong>RawData_Visibility.zip</strong> contains the raw count information obtained for the visibility curves, as expained in the Supplementary Information Sec. 2.1. The files follow the same naming convention as those in RawData_DelaySweep.zip. It also contains the file AnalysisCounts.py, which analyzes the data to obtain the correlation parameters.</p> <p> </p> <p>The file <strong>BellCorrelations_CompiledData.xlsx</strong> is a spreadsheet containing the results of the analysis of the previous two sets of data.</p>
Data set from ambient vibration monitoring and static loading of a steel stringer bridge subject to imposed damage
<p>This data set contains structural response measurements acquired from the Route 345 Bridge over Big Sucker Brook in Waddington, NY prior to demolition and replacement. This steel stringer bridge was instrumented with dual-axis accelerometers and strain transducers and response measurements were obtained prior to and following mechanically imposed damages. Accelerometer measurements were obtained under vehicle passes and strain measurements were acquired during static loading of the span with a truck positioned at three prescribed locations. All measurement data is contained in a single h5-file (hierarchical data format version 5). The data is shared with the intent of promoting the advancement of structural health monitoring and vibration-based damage detection. </p> <p><strong>Version 2 Note: </strong>This version corrects the strain measurement data. Due to an index counter error in the script that compiled the strain measurement data into the h5-file, the strain measurement data in the Version 1 data were incorrectly sourced from a single scenario. The strain measurements are corrected in this new version. No other changes were made in the h5-file.</p>
Data from: Energy harvesting in a flow-induced vibrating flapper with biomimetic gaits
<p>Energy harvesting from flow induced vibrations (FIV) in flexible bodies offer opportunities for power generation in biomimicking robotic devices and is an active area of research. The focus of this study is on investigating the underlying physics and qualitatively analysing the energy extraction scenarios in similar structural systems, comprising of a flexible piezoelectric flapper in a low Reynolds number flow regime. A high-fidelity three-way fully coupled fluid-structure-electric energy solver is developed in-house to study the energy harvesting capabilities of such a flapper, its hydrodynamic characteristics and the associated unsteady flow-field. The results indicate that the flapper deformation profiles at the most efficient harvesting regimes, resemble the propulsion gaits of natural swimmers. Investigations on the effects of a sinusoidal heaving actuation reveal no significant impact on the harvested power at the high yield (high power output) regime, identified under the passive condition showing biomimetic gait. This study provides mechanics based insights that is expected to be useful for bio-inspired designs of FIV based harvesters.</p>
Columns formwork acceleration during concrete vibration
<p>These datasets include the formwork accelerations of 5 columns during the vibration of the concrete as an indirect measure to estimate the vibration time. The measures are part of one of the demonstrators of the <a href="https://www.ashvin.eu/">ASHVIN</a> project, which aims to develop methodologies for implementing Digital Twins in the construction sector.</p>
Experimental absorption spectra used in "Spectral profile of ro-vibrational transitions of HCl broadened by He, Ar and SF6: testing the β-correction to the Hartmann-Tran profile and the speed dependent (complex) hard collision model"
<p>Experimental absorption spectra used in the article entitled <strong>"Spectral profile of ro-vibrational transitions of HCl broadened by He, Ar and SF<sub>6</sub>: testing the β-</strong><strong>correction to the Hartmann-Tran profile and the speed dependent (complex) hard collision model", </strong>to be published in the Journal of Quantitative Spectroscopy and Radiative Transfer. Accepted 19 March 2024.</p> <div> <div> <div> <div> <h3><a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jqsrt.2024.108977" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jqsrt.2024.108977</a></h3> </div> </div> </div> </div> <p> </p> <p>Comma separated ASCII files with 1 header line.</p> <p>First column is wavenumber in cm-1</p> <p>The rest of the columns contain the napierian absorbance at the total pressure given in the header. </p> <p>Mind the units!: pressure of Ar-mixtures is expressed in Torr, pressure of He- and SF6-mixtures is expressed in mbar</p> <p> </p>
Vibrating aggression: Spider males perform an unusual assessment strategy during contest displays
<p>A recurrent question in animal contests is whether individuals adopt a self or mutual assessment rule to decide to withdraw from a contest. However, many empirical studies fail to find conclusive support for one of these two possibilities. A possible explanation is that assessment strategies vary between individuals. In the contests of the orb-web spider <em>Trichonephila clavipes</em>, males perform a vibrational display on webs that may escalate to physical contact. Since all individuals perform the vibrational phase and only some of them escalate, we proposed two hypotheses: 1) all individuals perform mutual assessment during the vibrational phase, or 2) some individuals that do not escalate adopt self-assessment, while individuals that escalated adopt mutual assessment. To evaluate these hypotheses, we investigated the relationship between the duration of the vibrational phase and frontal leg length (a proxy of male fight capacity) of loser and winner males in contests that escalated and did not escalate to the physical contact phase. We found a non-significant relationship between duration and losers leg length for both contests that escalate and did not escalate. While we found a positive relationship between duration and winners leg length, particularly in contests that did not escalate. These results do not provide support for mutual assessment or for a mix of different assessment rules among individuals. We suggest that in <em>T. clavipes</em>, the dynamics of the vibrational phase may be explained by two different contest strategies (opponent-only assessment or size-based aggressiveness) that are dependent on intruder motivation to escalate.</p>
Good vibrations: Remote-tactile foraging success of wading birds is positively affected by the water content of substrates they forage in
<p>Some taxa of wading birds can locate buried prey by detecting vibratory cues in their foraging substrates while probe-foraging, using a sensory modality called "remote-touch". As more saturated substrates transmit vibrations better, we predict that these birds can detect prey in wetter substrates more easily. We used sensory assays to test whether substrate water content affects the remote-touch foraging success rate of Hadeda Ibises, <em>Bostrychia hagedash</em>. The birds were more successful at locating prey using vibratory cues than when relying on random direct contact with the beak alone. Their remote-touch foraging success rate was positively affected by increasing water contents of the soil, but water content had no effect on their direct contact foraging success (indicating this is not an artefact of ease of probing). This may partially explain the link between the range expansion of this species in southern Africa and increased soil irrigation, as it is easier for the birds to detect prey in wetter substrates. Thus, it is likely that the distribution of other remote-touch foraging birds is affected by substrate water content, and as many of these species are endangered and rely on sensitive wetland habitats, it is vital to understand their sensory requirements for foraging.</p>
AI4EU Robotics Pilot: Vibration sensor measurements in a robotic pump
<p>The robotic pump demonstrator represents a hydraulic pump that can be mounted on an industrial robot, for example, to pump liquid paint for spray painting. On this pump, one accelerometer is mounted for vibration monitoring and recording.</p> <p>The pump can be controlled in terms of speed (rotations per minute, rpm), affecting the throughput of paint and the pressure in and out of the pump.</p> <p>The dataset consists of 380 million measurements of several sensor data of the pump system in 1-second intervals over two months in 2020. The data is split by the recording date over 33 files.</p>
AI4EU Robotics Pilot: Vibration sensor measurements in a robotic wrist
<p>The robotic wrist demonstrator represents a mechanical wrist with three axes that can hold tools, e.g. for spray painting in combination with a pump. On this robotic wrist, two accelerometers are mounted for vibration monitoring and recording: one in the movable front part of the wrist and one in the shaft. The wrist can be controlled through the torque or the designated position of each axis’ motor.</p> <p>The dataset consists of 1.8 billion measurements of several sensor data of the robotic wrist in 1-second intervals over six months in 2020. The data is split by the recording date over 98 files.</p>
Vibration assisted drilling (VAD) application to the manufactured maraging steel X3NiCoMoTi18-9-5 (1.2709) and aluminium AlSi10Mg (EN AC-43000) parts
<p>Repository containing data from vibration assisted drilling (VAD) experiments on steel and Aluminum 3D powderbed manufactured parts.</p> <p>Please refer to README.MD (or .PDF), which contains a brief description of the chosen materials, parts and tools An explanation of the data aquisition and processing methods, together with the used nomenclature is given as well.</p>
Vibration and IMU Sensing Human Activity Dataset
<p>This dataset contains fine-grained human daily activity data collected by infrastructure vibration sensors and one on-wrist IMU sensor. This dataset is collected from six persons from two domestic homes, in total, there are 12 sub-datasets.</p> <p>For the naming, "p" means person and "l" means location.</p> <p>Each dataset has 11 columns, 1o of them stands for sensors' reading.</p> <p>* Due to the uploading platform, please<strong> <em>ignore</em> </strong>all files in the folder '__MACOSX', and files whose names start with '._'. These are computer system files, not parts of the shared dataset. </p> <p>** If you are going to use this dataset for any publications, we will appreciate you to cite this dataset properly.</p> <p>************************************************************</p> <p>The following content is copied from README.txt in the compressed folder:</p> <p>-----------------------<br> Labels:</p> <p>Keyboard typing 1<br> Using mouse 2<br> Handwriting 3<br> Cutting vegetables 4<br> Stir-frying vegetables 5<br> Wiping the table 6<br> Sweeping floor 7<br> Using vacuum to vacuum floor: 8<br> Open and close drawer: 9</p> <p>None Activity: 10</p> <p>-----------------------<br> 11 Columns:<br> 1: Activity label<br> 2: Vibration sensor put on the Living Area floor<br> 3: Vibration sensor put on the Living Area table<br> 4: Vibration sensor put on the Studying Area floor<br> 5: Vibration sensor put on the Studying Area desk<br> 6, 7, 8: Accelerometer X,Y,Z<br> 9, 10, 11: Gyroscope X,Y,Z</p> <p>-----------------------<br> All signals are zero-meaned.<br> The vibration sensors' sampling rate is roughly around 6500Hz, and the IMU sensors' original sampling rate is roughly around 235Hz.</p> <p>************************************************************</p> <p>New in Version 2:</p> <p>- Added extracted features from IMU data and vibration data for reference.</p> <p>- IMU signal is applied with a sliding window of 1.5 seconds with 0.75 seconds overlapping, then the feature is extracted in each window. The feature's description can be found here: https://dl.acm.org/doi/abs/10.1145/3410530.3414320</p> <p>- The vibration signal is applied with event detection to extract events in the vibration signal. For each event, we normalize it by its energy, then extract 10~490 Hz frequency amplitude as the feature.</p> <p> </p> <p>Disclaimer: Both event detection and feature extraction are empirical, we don't guarantee it is an optimal one.</p>
Vibrational coherences in half-broadband 2D electronic spectroscopy: spectral filtering to identify excited state displacements
<p>All data presented in the figures of "Vibrational coherences in half-broadband 2D electronic spectroscopy: spectral filtering to identify excited state displacements".</p>
Data from: Biomechanical properties of non-flight vibrations produced by bees
<p>Bees use thoracic vibrations produced by their indirect flight muscles for powering wingbeats in flight, but also during mating, pollination, defence, and nest building. Previous work on non-flight vibrations has mostly focused on acoustic (airborne vibrations) and spectral properties (frequency domain). However, mechanical properties such as the vibration's acceleration amplitude are important in some behaviours, e.g., during buzz pollination, where higher amplitude vibrations remove more pollen from flowers. Bee vibrations have been studied in only a handful of species and we know very little about how they vary among species. Here, we conduct the largest survey to date of the biomechanical properties of non-flight bee buzzes. We focus on defence buzzes as they can be induced experimentally and provide a common currency to compare among taxa. We analysed 15,000 buzzes produced by 306 individuals in 65 species and six families from Mexico, Scotland, and Australia. We found a strong association between body size and the acceleration amplitude of bee buzzes. Comparison of genera that buzz-pollinate and those that do not suggests that buzz-pollinating bees produce vibrations with higher acceleration amplitude. We found no relationship between bee size and the fundamental frequency of defence buzzes. Although our results suggest that body size is a major determinant of the amplitude of non-flight vibrations, we also observed considerable variation in vibration properties among bees of equivalent size and even within individuals. Both morphology and behaviour thus affect the biomechanical properties of non-flight buzzes.</p>
The Politecnico di Torino rolling bearing test rig: description of the open-access data for vibration monitoring and diagnostics
<p>Accelerometric measurements from the rolling bearing test rig of the Dynamic and Identification Research Group (DIRG), Department of Mechanical and Aerospace Engineering, Politecnico di Torino.</p> <p>Goals:</p> <p> • Vibration Monitoring, Bearing Diagnostics, Damage detection, Damage localization, Damage classification, Damage assessment.</p> <p>Features:</p> <p> • high-speed spindle driving a hollow shaft supported by a couple of identical roller bearings B1 and B3. B1 is the bearing under analysis and features various damages.</p> <p> • two damage types (indentations on a roller and on the inner ring) and severities (0, 150, 250, 450 µm).</p> <p> • a central, larger roller bearing (B2) is loaded through a sledge generating a controlled radial force measured by a load cell.</p> <p> • lubrication is obtained by oil injection into the hollow shaft.</p> <p> • a K-type thermocouple is used to monitor the temperature (manually recorded).</p> <p> • two triaxial accelerometers are mounted on the supports of bearings B1 and B2.</p> <p>Dataset:</p> <p> • stationary acquisitions at different speed & load combinations (speed: 0, 100, 200, 300, 400, 500 Hz; load: 0, 1000, 1400, 1800 N).</p> <p> • endurance acquisitions of the bearing featuring the 450µm roller indentation. Monitoring of the damage evolution for about 230 hours under the same speed and load condition.</p> <p> </p> <p>The extended description of the dataset can be found in the attached pdf "Description and analysis of open access data" or in:</p> <p>A.P. Daga, A. Fasana, S. Marchesiello, L. Garibaldi, The Politecnico di Torino rolling bearing test rig: Description and analysis of open access data, Mechanical Systems and Signal Processing 120 (2019) 252–273. doi:10.1016/j.ymssp.2018.10.010.</p>
3D printer audio and vibration side channels
<p>The dataset focuses on side channel data, i.e., sound and vibration, of 3D printers. The dataset aims to enable further research in cyber-physical system security and explore the vulnerability of fused deposition modeling to side chanel attacks.</p> <p>In particular, the datset consists mainly of sound and vibration data that were collected from two different 3D printers (bambu lab P1P and A1mini), using two different sensor systems. The first method is based on an iPhone, whereas the second one is based on a Teensy microcontroller. Both systems record sound at 44.1kHz sampling frequency. The vibrations are based on acceleration data sampled at 100 Hz and 500 Hz for the iPhone and the Teensy 4.0, respectively. Furthermore, the diversity of the dataset for both Teensy and iPhone methods was achieved using 12 different 3D designs. The dataset also inludes the source 3D CAD and sliced toolpath files of the objects that were printed, videos of the printing process, and recordings of the backround noise that exists in the data recordings. A table of contents is also provided in the files.</p>
Supporting Data for: The V30 Benchmark Set for Anharmonic Vibrational Frequencies of Molecular Dimers
<p>Intermolecular vibrations are extremely challenging to describe but are the most crucial part for determining entropy and hence free energies, and enable for instance the distinction between different crystal-packing arrangements of the same molecule via THz spectroscopy. Herein, we introduce a benchmark data set - V30 - containing 30 small molecular dimers with intermolecular interactions ranging from exclusively van-der-Waals dispersion to systems with hydrogen bonds. All calculations are performed with the gold standard of Quantum Chemistry CCSD(T). We discuss vibrational frequencies obtained via different models starting with the harmonic approximation over independent Morse oscillators up to second-order vibrational perturbation theory (VPT2), which allows a proper anharmonic treatment including coupling of vibrational modes. However, large amplitude motions present in many low-frequency intermolecular modes are problematic for VPT2. In analogy to the often used treatment for internal rotations, we replace such problematic modes by a simple one-dimensional hindered rotor model. We compare selected dimers with available experimental data or high-level calculations of potential energy surfaces and show that VPT2 in combination with hindered rotors can yield a very good description of fundamental frequencies for the discussed subset of dimers involving small and semi-rigid molecules.<br><br>This supporting dataset includes the calculated force constants, harmonic frequencies, Morse frequencies, VPT2 frequencies, and the optimized structures for the V30 dataset. See the included README.md file for more details. The related preprint can be found at <a href="https://doi.org/10.48550/arXiv.2209.04392">https://doi.org/10.48550/arXiv.2209.04392</a>.</p>
On-chip phonon-enhanced IR near-field detection of molecular vibrations
<p>This dataset contains the source data and raw interferograms associated with our manuscript, <em>'On-chip phonon-enhanced IR near-field detection of molecular vibrations</em>' by A. Bylinkin et al. The source data, provided in an .xlsx file, includes the datasets used to generate the figures in both the main text and the Supplementary Information. The raw interferogram dataset, located in the <em>'Interferograms</em>' folder, was used to calculate the experimental spectra shown in Fig. 3b, f, and Suppl. Fig. 13. This dataset was acquired using a NeaSNOM microscope (attocube AG).</p> <p>The data processing procedure for calculating spectra from the interferograms is described in the Methods section of our manuscript.</p>
Footstep-Induced Floor Vibration Dataset In Different Deployment Environment
<p>Footstep-induced floor vibration sensing has been used in many smart home applications, such as elderly/patient care, health monitoring. However, impact by the deployment environment, the acquired dataset in the different environments might have different characteristics. We utilize structural vibration sensing to acquire the footstep-induced floor vibration dataset under different humans, wearing different shoes, and in different environments. We also utilize wearable accelerometer sensing to capture the footstep event activity as the ground truth of the vibration dataset.</p> <p>The name format of each variable is as: "People ID_Environment ID_Sensor ID_Lane ID_Shoe ID". In this dataset, we have two human objects, eight environments, four sensors, three lanes, and three different shoes. You can find more details in our published paper.</p> <p>Each variable is a struct, and it contains four files: (1)'vibration': the raw vibration data (2,3,4)'IMU_X/Y/Z': the raw data of wearable accelerometer sensor.</p> <p>Currently, we have two papers published using this dataset [1,2].</p>
Dataset for: Similarity scores of vibrational spectra reveal the atomistic structure of pentapeptides in multiple basins
<p>This dataset provides input/output files and scripts for the publication: Similarity scores of vibrational spectra reveal the atomistic structure of pentapeptides in multiple basins.</p>
Matrices for a plate with tuned vibration absorbers
<p>Matrices for a numerical model of an aluminum plate equipped with tuned vibration absorbers (TVA).</p> <p>For usage see RUNME.m and the <a href="http://modelreduction.org/index.php/Plate_with_tuned_vibration_absorbers">MOR Wiki</a>.</p> <p>Version history:</p> <ul> <li>1.0: Initial release</li> <li>1.1: Added RUNME.py</li> </ul>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.